Load controller and method to enhance effective capacity of a photovoltaic power supply using a dynamically determined expected peak loading

ABSTRACT

A load controller and method are provided for maximizing effective capacity of a non-controllable, renewable power supply coupled to a variable electrical load also coupled to a conventional power grid. Effective capacity is enhanced by monitoring power output of the renewable supply and loading, and comparing the loading against the power output and a load adjustment threshold determined from an expected peak loading. A value for a load adjustment parameter is calculated by subtracting the renewable supply output and the load adjustment parameter from the current load. This value is then employed to control the variable load in an amount proportional to the value of the load control parameter when the parameter is within a predefined range. By so controlling the load, the effective capacity of the non-controllable, renewable power supply is increased without any attempt at operational feedback control of the renewable supply.

CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application comprises a continuation-in-part patentapplication of U.S. application Ser. No. 09/523,682, filed Mar. 10,2000, entitled “Load Controller and Method to Enhance Effective Capacityof A Photovoltaic Power Supply Using A Dynamically Determined ExpectedPeak Loading”, which itself is a continuation-in-part patent applicationof U.S. Pat. No. 6,037,758, issued Mar. 14, 2000, which claimed thebenefit of U.S. provisional application No. 60/083,230, filed Apr. 27,1998. U.S. application Ser. No. 09/523,682 and Letters Patent No.6,037,758 are hereby incorporated herein by reference in their entirety.

STATEMENT AS TO RIGHTS UNDER FEDERALLY SPONSORED RESEARCH

[0002] This invention was made with Government support under NRELSubcontract No. XAD-8-17671-01, Prime Contract No. DE-AC36-98GO10337awarded by The Department of Energy. Accordingly, the Government hascertain rights in this invention.

TECHNICAL FIELD

[0003] The present invention relates in general to a control apparatusand method for controlling a variable electric load which is supplied bya conventional power grid and a non-controllable, renewable power supplysuch as a photovoltaic power source, and more particularly, to a loadcontroller and method which seek to maximize effective capacity of therenewable power source.

BACKGROUND OF THE INVENTION

[0004] The practical use of photovoltaic systems, which convert incidentsunlight into electrical energy, continues to be of significant interestto the power generation industry. The development of more efficientsolar cells, as well as the lower production costs realized by themanufacture of continuously deposited, amorphous solar cells, has madephotovoltaic systems more realizable. Photovoltaic modules are beingcommercially used today to power devices such as radios, to tricklecharge batteries in parked cars, and in night illumination systems.

[0005] Photovoltaic arrays may be used in a wide variety of additionalsettings. In general, photovoltaics may be used remotely with specificloads (e.g., signal repeating towers) or with unspecific loads (e.g.,off-grid residences, off-grid villages), or connected to a power supplygrid. Further, a photovoltaics supply may be connected to a power grideither on the customer-side or on the utility-side of an electric meter,depending upon who owns the system. The present invention is directedprincipally to applications concerning function-unspecific loads,primarily, but not uniquely in the context of grid-connected systems andon either side of the meter.

[0006] High efficiency power conditioning units (PCUs) are commerciallyavailable today to ensure that photovoltaic arrays operate near theirmaximum power point. These PCUs maximize energy transfer from sunlightto usable AC electricity. Under actual conditions, a 1 kW rated array istypically capable of producing anywhere between 1300 and 2500 kWh peryear in the United States depending on local climate and array geometry.By contrast, an ideal generator working twenty-four hours per day wouldproduce 8760 kWh per year per rated kW. The ratio between thephotovoltaic array output and this ideal output is referred to ascapacity factor. Hence, for a photovoltaic array, the capacity factortypically ranges from 15% to 28%. Electrical power plants derive valuenot only from energy production (their capacity factor) but also fromtheir capacity, that is their contribution to a utility's spinningreserve, hence their ability to deliver power on demand.

[0007] Overall, the capacity value of an ideally dispatchable powerplant is of the same order as the value of the energy delivered by thatplant. Hence, the economics of photovoltaics have traditionally beenpenalized by the fact that no capacity value is considered for thisresource. The present invention is thus directed to capturing additionalvalue for photovoltaics (as well as other non-controllable, renewableresources) by increasing or even maximizing effective capacity of thenon-controllable power supply when coupled to a power grid.

DISCLOSURE OF THE INVENTION

[0008] Briefly summarized, this invention comprises in one aspect amethod for increasing effective capacity of a photovoltaic (PV) powersupply coupled to a power grid and a variable load so that the variableload is powered by the power grid and the PV supply. The methodincludes: determining photovoltaic power supply output and currentloading of the variable load, the current loading being determined as acurrent value of the variable load in the absence of the photovoltaicpower supply; determining an expected peak loading (EPL) of the variableload for a defined time interval and ascertaining therefrom a loadadjustment threshold; determining a value for a load adjustmentparameter from the photovoltaic power supply output, the currentloading, and the load adjustment threshold, the load adjustmentparameter being defined as the current loading less the photovoltaicpower supply output less the load adjustment threshold; and controllingthe variable load employing the value of the load adjustment parameter.This controlling of the variable loading is preferably proportional tothe value of the load adjustment parameter when the value is within apredefined range. The load adjustment parameter is employed to controlthe variable load so as to increase the effective capacity of thephotovoltaic power supply without any operational feedback control ofthe PV supply.

[0009] In another aspect, a load controller is provided implementing theabove-described method. This load controller controls a variable loadcoupled to a power grid and to a photovoltaic power supply. The loadcontroller includes means for: (i) determining photovoltaic power supplyoutput and current loading of the variable load, the current loadingbeing a current value of the variable load in the absence of thephotovoltaic power supply; (ii) determining an expected peak loading(EPL) of the variable load for a defined time interval and ascertainingtherefrom a peak adjustment threshold; (iii) determining a value for aload adjustment parameter based on the photovoltaic power supply output,the current loading, and the load adjustment threshold, the loadadjustment parameter being defined as the current loading less the PVsupply output less the load adjustment threshold; and (iv) controllingthe variable load employing the value of the load adjustment parameter.This controlling of the variable load is such as to increase theeffective capacity of the photovoltaic power supply.

[0010] To restate, the load controller/method of the present inventionenhances the economic feasibility of photovoltaic power plants byincreasing their “effective capacity” through minimal, selective controlof the load. Depending upon the geographical location, a load controllerin accordance with this invention can add up to $50-$100 per kilowattper year to the value of a demand-side photovoltaic power plant. Theload controller/method presented enhances the grid penetration potentialof a photovoltaic plant and enhances the acceptability of photovoltaicsto utility companies. In effect, the present invention proposesselectively reshaping utility load patterns to provide a better matchwith photovoltaic power output, thereby increasing the ultimate shareand reliability of photovoltaics in a utility power generation mix. Thisinvention thus enhances deployment opportunities for the moreenvironmentally benign photovoltaic industry. Additionally, the loadcontroller/method presented herein could be applied with otherenvironmentally benign, non-controllable but renewable resources, suchas wind power generation.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above-described objects, advantages and features of thepresent invention, as well as others, will be more readily understoodfrom the following detailed description of certain preferred embodimentsof the invention, when considered in conjunction with the accompanyingdrawings in which:

[0012]FIG. 1 is a simplified block diagram of a variable electric loadsupplied by a power grid and a non-controllable, renewable resource suchas a photovoltaic (PV) supply system;

[0013]FIG. 2 is a block diagram of a load controller in accordance withthe present invention shown with the system of FIG. 1;

[0014]FIG. 3 is a flowchart of one embodiment of processing to beimplemented by the load controller of FIG. 2; and

[0015]FIG. 4 is a more detailed embodiment of the control logicprocessing of FIG. 3 in accordance with the principles of the presentinvention.

BEST MODE FOR CARRYING OUT THE INVENTION

[0016] Generally stated, “capacity” is a measure of power (kW) that canbe “counted on” to meet load requirements. Even though photovoltaicarrays are capable of delivering a reasonable amount of energy, they aretraditionally assigned no capacity. This is because photovoltaic outputis dependent upon the weather and the cycle of days, and hence cannot becontrolled or dispatched to meet load requirements. However, asexplained herein, applicant has discovered that the “effective capacity”of a photovoltaic array can be quite high depending on the consideredload.

[0017] The “effective capacity” of a power plant is the kilowatt (kW)amount by which the power plant may be expected to contribute to thetotal kilowatt generating capacity available to an electricity providerto meet load requirements. The considered load requirements may beregional (utility), localized (sub-utility) or end-use. In the lattercase, when the considered power plant is located on the user-side of themeter, an alternate definition of effective capacity would be: thekilowatt amount by which the power plant may be expected to reduce theuser's kilowatt demand. Effective capacity can also be used in relative(percent) terms as the ratio between the kilowatt effective capacity andthe rated kilowatt capacity of the power plant.

[0018] Both energy and capacity are valuable commodities. On thecustomer side of an electric meter, large electrical users typicallyhave to pay for both as energy and demand. On the utility side of themeter, capacity is valued against the cost of building new power plants.In addition, when considering dispersed generation such as photovoltaicarrays, locally available capacity is valued against the cost ofmaintaining and upgrading transmission and distribution power lines,transformers, etc.

[0019] One initial challenge facing applicant is to identifyquantitative measures of effective capacity that best capture theability of a non-controllable resource to meet loads. Several benchmarkshave been developed and adapted for this purpose. First, an EffectiveLoad Carrying Capability (ELCC) parameter is defined as a primarybenchmark. This parameter is a probabilistic measure of availablecapacity that has traditionally been used by electric utilities toquantify the contribution of new power plants to the total capacityavailable to that utility under given loss of load probabilityconditions. The ELCC is a relative measure that can be reported inpercent of rated capacity. For instance, a photovoltaic power plant witha rated capacity of 1000 kW and ELCC of 60% could be considered as theequivalent of a 600 kW ideally dispatchable unit.

[0020] Note that the geographic regions of highest ELCC do notnecessarily overlap with regions of high solar energy resource. Forinstance, the mid-Atlantic seaboard features some of the highest ELCCs(e.g., 70%) in the United States. This region has not been noted for itshigh solar resource, however, while Florida with a much higher solarresource only achieves 40-50% ELCC.

[0021] Since the ELCC is a probabilistic measure, another benchmark isalso needed. This benchmark, referred to as the Minimum Buffer EnergyStorage (MBES), is defined as the minimum storage that would give ameasure of the ability of a photovoltaic to meet its load requirementsunder worst case conditions. Essentially, the MBES is the amount ofenergy reserve that would be necessary in addition to the photovoltaicpower plant to ensure that the photovoltaic power plant plus storagesystem could meet all loads above a given threshold, and hence deliveran effective capacity (ELCC) of 100%.

[0022] Through experimentation, applicant has discovered that for PVload penetration levels on the order of 5%, the amount of MBES could beas little as a fraction of a system hour. For instance, for New York'sCon Edison at 5% PV load penetration (i.e., 500 MW installedphotovoltaics) one-half hour worth of storage (250 MWh) would be enoughto register a 100% ELCC (i.e., meeting all loads above 95% of maximumdemand). By contrast, the amount of energy reserve to achieve the samecapacity without photovoltaics would be five system hours (2500 MWh).

[0023] The example above applies to utility-wide (i.e., regional) loadrequirements. At the regional level, applicant has discovered thateffective capacity is well correlated with specific load-shapecharacteristics (including the time of peak load and thesummer-to-winter peak load ratio).

[0024] Localized loads have also been investigated, includingsubstations and medium/large end-users. Applicant has discovered thatthe effective capacity of photovoltaic arrays, as quantified by the ELCCand MBES benchmarks, could be significant at this level as well. Therelationship between load characteristics and photovoltaic effectivecapacity has been found to remain the same for these smaller localizedloads. Among end-user types, the effective capacity is believed highestfor air-conditioned office buildings and hospitals. The fact thatlocalized and customer-side effective capacity can be controlled andremain significant has important economic implications. This means that,in addition to having utility-wide generating capacity value, aphotovoltaic array could also capture a transmission and distributionvalue (on the utility side), and/or demand reduction value (on thecustomer side).

[0025] More specifically, the MBES benchmark indicates that if aphotovoltaic array were operated under favorable conditions (forexample, in a commercial office building or metropolitansubstation/utility load) it would take only a small amount of energyreserve in addition to a photovoltaic power plant to increase effectivecapacity of the photovoltaic array to 100%. With demand rates as high as$30 kW for several large metropolitan utilities, this effective capacityincrease is significant.

[0026] Rather than supplying stored or backup energy to compliment aphotovoltaic array when needed to guarantee a high ELCC, the same effectis achieved in accordance with the principles of the present inventionby controlling the load energy by an amount equal to the amount thatwould otherwise be needed to guarantee a desired effective capacity.Based on the MBES values reported above, the necessary load reductionswould not have to be very large. Thus, a load controller in accordancewith the present invention may act, for example, on the setting of abuilding energy system (such as cooling, heating or lighting) and/orend-use appliance by slightly modifying the system or applianceoperating thresholds and/or operating schedules when needed to maintaineffective capacity. It is important to note that the present inventiondoes not seek to maximize the energy transfer from the photovoltaic tothe grid. Power conditioning units (PCUs) are already available toperform this function as described above. Further, it is important tonote that the present invention employs only an informational linkbetween the photovoltaic array output and the load controller to beimplemented.

[0027] In accordance with this invention, a load controller and methodare proposed which seek to indefinitely control a variable load in amanner that has not heretofore been addressed. A load controller inaccordance with this invention is designed to maximize a photovoltaicarray's “effective capacity” by selective load control. Prior approacheseither maximize energy transfer (for example, reference U.S. Pat. No.5,560,218) or maximize power tracking (for example, reference U.S. Pat.No. 5,293,447), i.e., the ability of a photovoltaic battery to operateat its optimum point on an I-V curve. In the context of a loadcontroller of the present invention, it is assumed that commerciallyavailable power conditioning units already maximize energy transfer fromthe photovoltaic plant to the AC power grid. The load controllerpresented herein is only concerned with the “effective capacity” of thephotovoltaic array.

[0028] Further, load control with a photovoltaic plant is typicallydirectly linked to a specific load (e.g., an air-conditioner).Conventional load control action involves feedback to the photovoltaicpower plant's operation because the action taken on the load optimizesenergy transfer from the power plant. This is to be contrasted with aload controller as presented herein. Pursuant to this invention, the PVpower plant operates totally independently of the load controller. Thelink to the load controller is informational only. In fact, thephotovoltaic plant and the load controller would not need to beco-located. For example, a utility operating a photovoltaic power plantcould employ a load controller as presented herein to meet the loadrequirements of a summer peaking substation. Load control units (e.g.,smart thermostats) installed at major customers served by the substationcould be used to maximize the photovoltaic plant's effective capacity,and hence its support to the substation and the downstream distributionline, without any feedback on the operation of the photovoltaic powerplant.

[0029]FIG. 1 depicts one embodiment of an electrical system 10 wherein apower grid 12 supplies power to a variable load 14 and a photovoltaic(PV) supply system 16 supplements power grid 12. A utility meter 18(shown in phantom) is typically disposed between power grid 12 and thevariable load 14. When disposed as shown in FIG. 1, the PV supply system16 is connected on the customer-side of the meter. Alternatively, system16 could be located on the utility-side of the meter depending upon whoowns the photovoltaic system.

[0030]FIG. 2 depicts one embodiment of a system 20 in accordance withthe present invention wherein a load controller 22 is coupled to PVsupply system 16 and variable load 14′ for monitoring PV supply system16 and load 14′, and for controlling variable load 14′ in order toincrease or maximize “effective capacity” of the PV supply system 16. Asnoted, this is achieved without any feedback control of the PV supplysystem itself. If desired, a user interface 24 can be coupled to loadcontroller 22 for facilitating user modification of one or moreparameters (discussed below) employed in the control algorithmimplemented by load controller 22.

[0031] A high level diagram of one embodiment of the control logicimplemented by controller 22 is depicted in FIG. 3. The logical nodes ofcontrol logic 50 are information 52, decision 54 and action 58.Information 52 gathers/comprises the input required to operate thecontroller's logic. This input consists of, for example, real-timeoutput of the photovoltaic power plant 40 and the real-time electricalload 30. Alternatively, the information may consist of proxies for thephotovoltaic array output and the current load. For example,photovoltaic output proxies may include solar radiation information,cloud cover images sensed by weather satellites, etc., while loadinformation proxies may comprise ambient temperature (which may behighly correlated with air-conditioning loads), time-of-day,time-of-week, and/or day-of-year information, etc. Note also that in autility-side context, the relevant photovoltaic output may consist ofthe combined output of several disbursed photovoltaic plants affectingthe considered load.

[0032] The photovoltaic and load information is fed to the controllerlogic, for example, through dedicated signal wiring, wireless signaltransmission, or power wires. The decision 54, which is described belowwith reference to FIG. 4, is made with reference to a contextual setting56. The context indicates whether the load controller is used in ademand-side or a utility-side mode. In a demand-side context, the loadcontroller is operated to maximize photovoltaic effective capacity withrespect to the customer's electrical load, while in a utility-sidecontext, the load controller is operated to maximize photovoltaiceffective capacity with respect to loads upstream from the customer, forexample, a local feeder, local substation load, or a utility-wide load.

[0033] Depending on the context and type of load controller application,decision 54 could be co-located with the action 58 or not. For instance,in a utility-side context, the decision could be made by a centralutility-operated logical unit, sending signals to localized actiondevices. The load controller can operate with either a deterministic ora probabilistic approach. In a deterministic approach, the action mightbe an adjustment of a selected operating threshold. Positive action isthe action of adjusting the operating threshold, preferably up to amaximum user-selected amount (maximum positive action (MPA)) in thesense of load reduction (e.g., raising operating temperature of anair-conditioned building). As explained further below, negative actionmay also be employed which could consist of a slight thresholdadjustment tending to increase the load, or no action might be taken onthe load depending upon the results of the decision logic.

[0034] In a probabilistic approach, take “negative action” (NA) mightsignify no pause or delay in the operation/startup of a given loadcomponent, such as an appliance or system. Maximum positive action (MPA)signifies enforcing a maximum delay/pause length on all consideredappliances or components of the load. Further, in accordance with thisinvention, positive action (PA) is preferably prorated to the value of aload control parameter between zero and A. This would imply enforcingpartial delay on all considered load components and/or more likely,enforcing a preset delay on a prorated fraction of the consideredappliances or load components. Additionally, those skilled in the artwill note that a probabilistic action may also comprise a thresholdadjustment as described above in connection with a deterministic action.

[0035] The choice/effectiveness of the control strategy depends on thecontext of the load controller application. For a user-owned demand-sidephotovoltaic system, a deterministic strategy might be preferable(unless the user is very large with many diversified loads) because theeffective capacity of the photovoltaic array, valued against the user'sdemand, could have a direct impact on the local load. Both strategieswould be effective in the context of a utility-owned or operated systembecause the impact on effective capacity would not need to be highlylocalized.

[0036]FIG. 4 depicts one example of decision logic in accordance withthe present invention. The decision per se is a decision whether to takeaction and if so, the type and magnitude of the action. The decision isimplemented automatically and is preferably repetitively re-evaluated ata predefined interval of time (e.g., every 2-5 minutes). This embodimentof the decision logic employs seven input parameters or variables.First, the real-time loading (or an approximation thereof) 30 as well asthe real-time photovoltaic array output (or an approximation thereof) 40are obtained. Note that the current load used as input is the loadunaffected by the controller (i.e., if measured, the load should beadjusted to reflect the action taken by the controller). In addition,the decision logic receives certain predefined, user-adjustable values.These values include the expected peak loading (EPL) 60 and thepercentage of photovoltaic penetration (PPV) 62, as well as twoconstants, A 64 and B 66, and a programmable maximum possible action(MPA) 67.

[0037] The EPL is assumed valid for a defined period of time, and can bebased on historical data, forecasts or even dynamically calculated asexplained further below. The PPV is a ratio of the size of thephotovoltaic generator (or ensemble of considered generators) to theconsidered peak load. It is important to note that the PPV could be afraction or a multiple of the size of the PV generator which issignificant with respect to a probabilistic load controller operation.Constant A is a multiplier to the size of the photovoltaic generator,adjusting the load control threshold for maximum action, while constantB is a multiplier to the size of the photovoltaic generator and is usedto decide between no action and negative action (described below).

[0038] Assuming that the above-described inputs are available, decisionlogic in accordance with the present invention determines a loadadjustment parameter X as follows:

X=(LOAD−PV−EPL·(1−PPV))/(EPL−PPV)

[0039] where:

[0040] LOAD=current load (known or determined from proxy). The term mayrefer to either the current reading of a considered load on a presetdata sampling time step (e.g. every minute), or to an average of thisvalue representative of a demand-sampling interval (e.g., 15 minutes isthe prevailing interval for most utilities in the United States). Inaddition, this term should reflect the load of the building as it wouldbe measured without photovoltaic (PV) or load control action. Therefore,LOAD should be equal to the measured building load(LD)+PV+XPCT·EPL−PPV,if the PV is on the customer side of the meter, and equal to buildingload(LD)+XPCT·EPL−PPV, otherwise;

[0041] PV=current measured PV output (known or determined from proxy)corresponding to the considered context;

[0042] XPCT·EPL·PPV=SLCLD=estimated load adjustment (e.g., curtailment)due to the solar load controller (of the present invention).

[0043] EPL=expected peak load (depending on context, this may be aseasonal or daily forecast, or an estimated yearly or seasonal valuebased on historical end-use bills). For most applications, EPL isadjusted dynamically from an initial estimate EPL₀ set at the beginningof a defined time interval, such as a billing cycle. Initial estimatesare user-set and may vary at the beginning of each defined interval. Onemethodology to dynamically adjust EPL within a defined interval frominitial value estimates for EPL and PPV, i.e., EPL₀ and PPV₀,respectively, would be as follows: Set EPL=EPL₀ If LOAD > EPL thenEPL=LOAD PPV=PPV₀·EPL₀/EPL Else No Change;

[0044] PPV=percentage of PV penetration determined by the ratio of theinstalled PV capacity and the peak of the considered load (depending onthe load control strategy and context, parameter PPV could also be anarbitrary portion of the PV generator.) When EPL is adjusted dynamicallyas explained above, PPV should be adjusted as well from an initial valuePPV₀, so that it always represents the ratio of installed PV capacity toEPL or any set multiple thereof. This action would be as specified underthe definition for EPL provided above.

[0045] In addition, because many applications are designed to reduceutility demand bills, and because demand is typically measured on a 15minute average basis, many of the above-defined parameters, includingthe measured building load (LD), the current measured photovoltaicoutput (PV), and the estimated load adjustment due to the solar loadcontroller (SLCLD) can be 15 minute rolling averages.

[0046] To restate, described herein is a technique for minimizing userdiscomfort while maximizing photovoltaic effective capacity. Forexample, in accordance with the algorithm described above, preset oruser adjustable values of EPL and PPV, referred to herein as EPL₀ andPPV₀, respectively, comprise preset values representative of anestimated guess of a buildings peak load during a given definedinterval, such as a billing cycle. These preset values may vary frombilling cycle to billing cycle. For example, the values could be storedin memory as user adjustable arrays of 12 month values. At the beginningof each demand billing cycle (i.e., a month or a year depending onutility tariffs), EPL and PPV are set to EPL₀ and PPV₀, respectively. Asmonitored input, LOAD and PV, become available, the controller can takeaction to fine tune EPL, i.e., both EPL and PPV can be adjusted as afunction of the actual monitored LOAD whenever the actual LOAD exceedsthe EPL. By this action, the algorithm proposed herein evolves with thebuilding and seeks to minimize the impact of the load controller on theuser. A goal is to maintain a demand reduction commensurate with thesite of the PV system irrespective of the peak load for a giveninterval.

[0047] Note that in effect the quantity EPL−(1−PPV) constitutes adecision threshold against which to gauge current load and PV outputconditions. Upon calculating the load adjustment parameter X 68, thedecision logic inquires whether the value of parameter X is greater than0 70. If parameter X is negative, meaning that the loading is less thanthe photovoltaic output plus the load adjustment threshold as definedabove, then (optionally) processing determines whether the loadadjustment parameter X is less than a predefined constant B, whichitself comprises a negative number 72. If parameter X is not less thanconstant B then no action 74 is taken and the decision logic returns Q76 by an appropriate link to the action center (for example, athermostat). However, if parameter X is less than the predefinedconstant B, processing is (optionally) directed to take “negativeaction” (NA) 78. If the action is deterministic, a negative action mightbe a preset adjustment of the considered operating threshold in thesense of a load increase (for example, lowering operating temperature ofan air-conditioned building). If action is probabilistic, then negativeaction might signify no pause or delay in the operation/startup of theconsidered load component. After deciding to take negative action,processing proceeds to the action center via an appropriate link Q 76.

[0048] Returning to inquiry 70, if the load adjustment parameter X is apositive number, then the decision logic next determines a value forvariable XPCT 82. XPCT is a factor between zero and one whichessentially prorates the positive action to be taken relative to amaximum possible action (MPA), i.e., XPCT is defined as min(1, X/A).After determining XPCT, processing determines a positive action (PA) tobe taken 84. In this example, positive action (PA) is a load controllerdetermined fraction of the maximum positive action up to the maximumpositive action. Thus, the load action taken in accordance with thisinvention will be prorated in many instances relative to the maximumpositive action predefined for the load controller. Once the positiveaction (PA) is determined, processing is passed to the action center Q76 for implementation of a deterministic or probabilistic action asdescribed above.

[0049] By way of example, one of ordinary skill in the art willunderstand that the present invention can be implemented employing a“smart thermostat”. The smart thermostat is a conventional thermostatthat would have the capability of receiving logic-driven signals andadjusting user-set temperature upwards or downwards, depending on thelogic's decisions. The example presented below assumes a demand-sidephotovoltaic system.

[0050] In one example, the LOAD and PV output could either be measuredor estimated from proxies (e.g., outdoor temperature, time of day and/ora photometer installed on the end-user's premises). A logic unit,installed in a central location (e.g., near an HVAC center, or near thePV power conditioning unit) would interpret this information, determinethe value of X, and send a series of pre-determined signals to the roomthermostat. These signals would correspond to amounts by which toincrease or reduce user-selected temperatures. Action orders would besent to the thermostats via thermostatic wire or any other appropriatemeans. In the case of decentralized HVAC units (e.g., room HVAC unitsused in many hotels), action orders could be sent through power wire tothe HVAC units, and appropriately relayed through thermostatic wires.The EPL parameter used in this example could simply be a conservativefraction of the expected building peak load based on simulation orhistorical demand bills. The PPV parameter would be the ratio ofinstalled PV capacity to the expected building peak load or afraction/multiple thereof.

[0051] As another example, one of ordinary skill in the art willunderstand that the present invention could be implemented as a smartlight controller. In this case, the maximum possible action (MPA) wouldrefer to the maximum acceptable level of light dimming. The algorithmwould, as described above, determine the parameter X and applyappropriate dimming as a fraction of a preset MPA.

[0052] As still another example, one of ordinary skill in the art willunderstand that the present invention could be implemented as an airconditioning controller. In this case, the maximum possible action (MPA)would refer to the maximum acceptable level of temperature change, e.g.,of temperature increase. The algorithm would, as described above,determine the parameter X and apply appropriate temperature changes as afraction of a preset MPA.

[0053] For those instances where MPA is not explicitly defined in termsof power (KW), and in particular, for a temperature cooling example, aparameter KWD can be employed. This parameter, which is auser-selectable input to the solar load control algorithm, representsthe expected amount of kilowatt load reduction resulting from one degreeof cooling temperature increase for the variable load. This parametermay be estimated for a particular building based upon (a) past bills,and/or (b) building load data, and/or (c) building and HVACspecifications. When the MPA is defined in temperature degrees, theestimated load curtailment resulting from action of the solar loadcontroller (SLCLD) equals PA·KWD, where PA is a temperature adjustmentrequest, i.e., the current PA is parameter X.

[0054] As a further consideration, it has been observed that abuilding's response to thermostatic temperature increase is notinstantaneous, but rather can take several minutes. In view of this, twoadditional parameters are defined, i.e., SLCLD_(long) and SLCLD_(short).SLCLD_(long) is defined as a running mean average of PA·KWD over Nminutes, where N is a user estimated amount of time necessary for athermostatic temperature adjustment to have a full impact on the load.SLCLD_(short) is defined as a running mean average of PA·KWD over Mminutes, where M is a user defined shorter time interval than N. Forexample, M may equal 2 minutes, while N may be 30 minutes. Further, twodistinct load parameters are defined, LOAD and LOAD′, as:

LOAD=LD+PV+Min(SLCLD _(short) , SLCLD _(long))

LOAD′=LD+PV+Max(SLCLD _(short) , SLCLD _(long))

[0055] where:

[0056] LOAD=a parameter used to update a value for the expected peakloading (EPL), discussed above;

[0057] LOAD′=a parameter used to calculate the parameter X (i.e.,PA_(now));

[0058] LD=measured value of the variable load;

[0059] PV=measured photovoltaic power supply output;

[0060] SLCLD_(short)=running mean average of PA·KWD over N minutes;

[0061] SLCLD_(long)=running mean average of PA·KWD over M minutes, whereM<N.

[0062] In order to avoid rapid cycling of HVAC equipment using a solarload controller as described herein, a degree of inertia can beintroduced into the temperature adjustment request (PA). In cases wherethe current request calculated from the parameter X (PA_(now)) issmaller than the previous request (PA_(old)), the following rule canapply:

PA=Max(PA _(now) , PA _(old) −MPA/q)

[0063] where q is a user-selected parameter. For example q may equal 10.

[0064] As a further consideration, a request for indoor temperatureincrease (PA) during the cooling season should result in a drop incooling load. However, some building HVAC control systems put occupantcomfort as a priority and a request for temperature increase may incertain systems result in the addition of heat (e.g., from a furnace)into the occupied space. This obviously could mitigate or eliminate anybenefit from a solar load controller as described herein. Therefore, anycall for heat should be intercepted by any appropriate means any time arequest for thermostatic temperature increase is generated by a solarload controller such as described herein used when cooling a building.

[0065] Those skilled in the art will note from the above description,that a load controller/method in accordance with the present inventionenhances the economic feasibility of non-controllable power plants bycontrollably increasing their “effective capacity” through selectivecontrol of the load. Depending upon the geographical location, a loadcontroller in accordance with this invention can add up to $50-$100 perkilowatt per year to the value of a demand-side photovoltaic powerplant. The load controller/method enhances the grid penetrationpotential of a photovoltaic plant and enhances the acceptability ofphotovoltaics to utility companies. In effect, the present inventionproposes selectively and dynamically reshaping utility load patternsover an indefinite period of time to provide a better match withphotovoltaic power output, thereby increasing the ultimate share andreliability of photovoltaics in a utility power generation mix. Thepresent invention thus enhances deployment opportunities for the moreenvironmentally benign photovoltaic industry. Additionally, the loadcontroller/method presented herein could be applied with otherenvironmentally benign, non-controllable but renewable resources, suchas wind power generation.

[0066] While the invention has been described in detail herein inaccordance with certain preferred embodiments thereof, manymodifications and changes therein may be effected by those skilled inthe art. Accordingly, it is intended by the appended claims to cover allsuch modifications and changes as fall within the true spirit and scopeof the invention.

What is claimed is:
 1. A method for increasing effective capacity of aphotovoltaic power supply coupled to a power grid and a variable load,said variable load being powered by said power grid and saidphotovoltaic power supply, said method comprising: (a) determiningphotovoltaic power supply output and current loading of said variableload, the current loading being a current value of the variable load inthe absence of the photovoltaic power supply; (b) determining anexpected peak loading of said variable load for a defined time intervaland ascertaining therefrom a load adjustment threshold; (c) determininga value for a load adjustment parameter from said photovoltaic powersupply output, said current loading and said load adjustment threshold,said load adjustment parameter being defined as said current loadingless said photovoltaic power supply output less said load adjustmentthreshold; and (d) controlling said variable load employing said valueof said load adjustment parameter to increase the effective capacity ofsaid photovoltaic power supply without operational feedback control ofsaid photovoltaic power supply.
 2. The method of claim 1, wherein saiddetermining (a) further comprises determining the current loading of thevariable load in the absence of the photovoltaic power supply and in theabsence of the controlling (d) of the variable load.
 3. The method ofclaim 1, wherein said determining (b) comprises setting an initialexpected peak loading at a start of the defined time interval andreevaluating the expected peak loading within the defined time intervalwith reference to variations in the variable load, said reevaluatingcomprising increasing the expected peak loading when the variable loadexceeds the expected peak loading, and wherein said reevaluating andincreasing comprise: If LOAD > EPL then EPL=LOAD PPV=PPV₀ · EPL₀/EPLElse No Change

wherein: LOAD=the variable load=LD+PV+SLCLD; LD=measured value of thevariable load; PV=measured photovoltaic power supply output;SLCLD=estimated load change due to said controlling (d) EPL₀=initialexpected peak loading at a start; of the defined time interval;EPL=expected peak loading variable; PPV₀=initial percentage ofphotovoltaic penetration determined by a ratio of installed photovoltaiccapacity and peak of the variable load or a fraction thereof; andPPV=current percentage of photovoltaic penetration determined by theratio of the installed photovoltaic capacity and the peak of the load ora fraction thereof.
 4. The method of claim 3, wherein the measured valueof the variable load (LD), the measured photovoltaic power supply output(PV), and the estimated load change due to said controlling (d) (SLCLD)are determined as rolling averages within a defined measurement timeinterval.
 5. The method of claim 1, wherein: said controlling (d)comprises adjusting current loading of the variable load if the value ofthe load adjustment parameter exceeds zero, wherein said adjusting isproportional to said value; said controlling (d) further comprisesadjusting an operating threshold of at least one load component of thevariable load; said method further comprises predefining a maximumpossible action and wherein said adjusting of said operational thresholdcomprises adjusting said operational threshold proportional to saidvalue up to said maximum possible action; and wherein said variable loadcomprises a temperature load, and said maximum possible action comprisesa maximum acceptable level of temperature change.
 6. The method of claim5, wherein said determining (a) further comprises determining thecurrent loading of the variable load in the absence of the photovoltaicpower supply and in the absence of the controlling (d) of the variableload, said controlling (d) of the variable load resulting in anestimated load change determined as: SLCLD=PA·KWD wherein:SLCLD=estimated load change due to said controlling (d) PA=a currentamount of operational threshold adjustment by said adjusting; andKWD=expected amount of kilowatt load reduction of the variable loadresulting from a degree of temperature change.
 7. The method of claim 6,further comprising defining two parameters SLCLD_(long) andSLCLD_(short), wherein SLCLD_(long) is a running mean average of PA·KWDover N minutes, where N is a user estimated amount of time necessary fora temperature adjustment to have full impact on the variable load, andSLCLD_(short) is a running mean average of PA·KWD over M minutes, whereM is a user defined time interval, and M<N; and wherein:LOAD=LD+PV+Min(SLCLD _(short) , SLCLD _(long)) LOAD′=LD+PV+Max(SLCLD_(short) , SLCLD _(long)) where LOAD=a parameter used to update a valuefor the expected peak loading determined by said determining (b);LOAD′=a parameter used to calculate the parameter PA (i.e., a currentamount of operational threshold adjustment by said adjusting);LD=measured value of the variable load PV=measured photovoltaic powersupply output SLCLD_(short)=running mean average of PA·KWD over Nminutes; SLCLD_(long)=running mean average of PA·KWD over M minutes,where M<N.
 8. The method of claim 1, wherein: said controlling (d)comprises adjusting current loading of the variable load if the value ofthe load adjustment parameter exceeds zero, wherein the adjusting isproportional to said value; said controlling (d) further comprisesadjusting an operating threshold of at least one load component of thevariable load; said method further comprises predefining a maximumpossible action and wherein said adjusting of said operational thresholdcomprises adjusting said operational threshold proportional to saidvalue up to said maximum possible action; wherein said variable loadcomprises a temperature load, and said maximum possible action comprisesa maximum acceptable level of temperature change; and wherein: PA=Max(PA_(now) , PA _(old) −MPA/q) where: PA=a temperature adjustment request;PA_(now)=is a current temperature adjustment request PA_(old)=is aprevious temperature adjustment request MPA=predefined maximum possibleaction q=a user selected parameter.
 9. The method of claim 1, whereinthe variable load comprises a variable cooling temperature load, saidcontrolling (d) further comprises adjusting an operating threshold of atleast one load component of the variable load, and wherein when saidadjusting results in an increase in cooling temperature, said increasein cooling temperature being accomplished without use of any heatingsystem associated with the variable load.
 10. A load controller forcontrolling a variable load coupled to a power grid and a photovoltaicpower supply, said load controller comprising: (i) means for determiningphotovoltaic power supply output and current loading of the variableload, said means for determining (i) comprising means for ascertaining acurrent value of the variable load in the absence of the photovoltaicpower supply; (ii) means for determining an expected peak loading ofsaid variable load for a defined time interval and for ascertainingtherefrom a load adjustment threshold; (iii) means for determining avalue for a load adjustment parameter based on said photovoltaic powersupply output, said current loading, and said load adjustment threshold,said load adjustment parameter being defined as said current loadingless said photovoltaic power supply output less said load adjustmentthreshold; and (iv) means for controlling said variable load employingsaid value of said load adjustment parameter to increase the effectivecapacity of said photovoltaic power supply.
 11. The load controller ofclaim 10, wherein said means for determining (i) further comprises meansfor determining the current loading of the variable load in the absenceof the photovoltaic power supply and in the absence of the means forcontrolling (iv) the variable load.
 12. The load controller of claim 10,wherein said means for determining (ii) comprises means for setting aninitial expected peak loading at a start of the predefined time intervaland for reevaluating the expected peak loading within the defined timeinterval with reference to variations in the variable load, said meansfor reevaluating comprising means for increasing the expected peakloading when the variable load exceeds the expected peak loading, andwherein said means for reevaluating and means for increasing comprise:If LOAD > EPL then EPL = LOAD PPV=PPV₀ · EPL₀/EPL Else No Change

wherein: LOAD=the variable load=LD+PV+SLCLD; LD=measured value of thevariable load; PV=measured photovoltaic power supply output;SLCLD=estimated load change due to said means for controlling (iv);EPL₀=initial expected peak loading at a start of the defined timeinterval; PPV₀=initial percentage of photovoltaic penetration determinedby a ratio of installed photovoltaic capacity and peak of the variableload or a fraction thereof; and PPV=current percentage of photovoltaicpenetration determined by the ratio of the installed photovoltaiccapacity and the peak of the load or a fraction thereof.
 13. The loadcontroller of claim 12, wherein the measured value of the variable load(LD), the measured photovoltaic power supply output (PV), and theestimated load change due to said means for controlling (iv) (SLCLD) aredetermined as rolling averages within a predefined measurement timeinterval.
 14. The load controller of claim 10, wherein: said means forcontrolling (iv) comprises means for adjusting current loading of thevariable load if the value of the load adjustment parameter exceedszero, wherein said adjusting is proportional to said value; said meansfor controlling (iv) further comprises means for adjusting an operatingthreshold of at least one load component of the variable load; said loadcontroller comprises means for predefining a maximum possible action andwherein said means for adjusting said operational threshold comprisesmeans for adjusting said operational threshold proportional to saidvalue up to said maximum possible action; and wherein said variable loadcomprises a temperature load, and said maximum possible action comprisesa maximum acceptable level of temperature change.
 15. The loadcontroller of claim 14, wherein said means for determining (i) furthercomprises means for determining the current loading of the variable loadin the absence of the photovoltaic power supply and in the absence ofsaid means for controlling (iv) the variable load, said means forcontrolling (d) the variable load resulting in an estimated load changedetermined as: SLCLD=PA·KWD wherein: SLCLD=estimated load change due tosaid means for controlling (iv) PA=current amount of operationalthreshold adjustment by said means for adjusting; and KWD=expectedamount of kilowatt load reduction of the variable load resulting from adegree of temperature change.
 16. The load controller of claim 15,wherein two parameters SLCLD_(long) and SLCLD_(short) are defined,SLCLD_(long) being a running mean average of PA·KWD over N minutes,where N is a user estimated amount of time necessary for a temperatureadjustment to have full impact on the variable load, and SLCLD_(short)being a running mean average of PA·KWD over M minutes, where M is a userdefined time interval, and M<N; and wherein: LOAD=LD+PV+Min(SLCLD_(short) , SLCLD _(long)) LOAD′=LD+PV+Max(SLCLD _(short) , SLCLD_(long)) where LOAD=a parameter used to update a value for the expectedpeak loading determined by said means for determining (ii); LOAD′=aparameter used to calculate the parameter PA (i.e., a current amount ofoperational threshold adjustment by said adjusting); LD=measured valueof the variable load PV=measured photovoltaic power supply outputSLCLD_(short)=running mean average of PA·KWD over N minutes;SLCLD_(long)=running mean average of PA·KWD over M minutes, where M<N.17. The load controller of claim 10, wherein: said means for controlling(iv) comprises means for adjusting current loading of the variable loadif the value of the load adjustment parameter exceeds zero, wherein theadjusting is proportional to said value; said means for controlling (iv)further comprises means for adjusting an operating threshold of at leastone load component of the variable load; said load controller furthercomprises means for predefining a maximum possible action and whereinsaid means for adjusting of said operational threshold comprises meansfor adjusting said operational threshold proportional to said value upto said maximum possible action; wherein said variable load comprises atemperature load, and said maximum possible action comprises a maximumacceptable level of temperature change; and wherein: PA=Max(PA _(now) ,PA _(old) −MPA/q) where: PA=a temperature adjustment request;PA_(now)=is a current temperature adjustment request PA_(old)=is aprevious temperature adjustment request MPA=predefined maximum possibleaction q=a user selected parameter.
 18. The load controller of claim 10,wherein the variable load comprises a variable cooling temperature load,said means for controlling (iv) further comprises means for adjusting anoperating threshold of at least one load component of the variable load,and wherein when said means for adjusting results in an increase incooling temperature, said increase in cooling temperature beingaccomplished without use of any heating system associated with thevariable load.